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Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines

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Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines

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dc.contributor.author Munera, S. es_ES
dc.contributor.author Blasco Ivars, J. es_ES
dc.contributor.author Amigo, J.M. es_ES
dc.contributor.author Cubero-García, Sergio es_ES
dc.contributor.author Talens Oliag, Pau es_ES
dc.contributor.author Aleixos Borrás, María Nuria es_ES
dc.date.accessioned 2020-03-06T13:25:28Z
dc.date.available 2020-03-06T13:25:28Z
dc.date.issued 2019-06 es_ES
dc.identifier.issn 1537-5110 es_ES
dc.identifier.uri http://hdl.handle.net/10251/138470
dc.description.abstract [EN] The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. 'Big Top' (yellow flesh) and 'Magique' (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630-900 nm using transmittance mode during their ripening under controlled conditions. The detection of split pit disorder and classification according to an established firmness threshold were performed using PLS-DA. The prediction of the Internal Quality Index (IQI) related to ripeness was performed using PLS-R. The most important variables were selected using interval-PLS. As a result, an accuracy of 94.7% was obtained in the detection of fruits with split pit of the 'Big Top' cultivar. Accuracies of 95.7% and 94.6% were achieved in the classification of the 'Big Top' and 'Magique' cultivars, respectively, according to the firmness threshold. The internal quality was predicted through the IQI with R-2 values of 0.88 and 0.86 for the two cultivars. The results obtained indicate the great potential of hyperspectral transmittance imaging for the assessment of the internal quality of intact nectarines. es_ES
dc.description.sponsorship This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00. Sandra Munera thanks INIA for the FPI-INIA grant num. 43 (CPR2014-0082), partially supported by European Union FSE funds. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Biosystems Engineering es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Stone fruit es_ES
dc.subject Split pit es_ES
dc.subject Ripeness es_ES
dc.subject Internal quality es_ES
dc.subject Hyperspectral imaging es_ES
dc.subject Computer vision es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.biosystemseng.2019.04.001 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//RTA2015-00078-00-00/ES/Sistemas no destructivos para la determinación automática de la calidad interna de frutas en línea utilizando métodos ópticos e información espectral/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/INIA//CPR2014-0082/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments es_ES
dc.description.bibliographicCitation Munera, S.; Blasco Ivars, J.; Amigo, J.; Cubero-García, S.; Talens Oliag, P.; Aleixos Borrás, MN. (2019). Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines. Biosystems Engineering. 182:54-64. https://doi.org/10.1016/j.biosystemseng.2019.04.001 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.biosystemseng.2019.04.001 es_ES
dc.description.upvformatpinicio 54 es_ES
dc.description.upvformatpfin 64 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 182 es_ES
dc.relation.pasarela S\383876 es_ES
dc.contributor.funder Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


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